---
title: Backend Tools
icon: "lucide/Server"
description: Render your agent's tool calls with custom UI components.
---
import { Accordions, Accordion } from "fumadocs-ui/components/accordion";
import { IframeSwitcher } from "@/components/content"
import { Tabs, Tab } from "fumadocs-ui/components/tabs"
import DefaultToolRendering from "@/snippets/shared/guides/default-tool-rendering.mdx"
import RunAndConnect from "@/snippets/integrations/agno/run-and-connect.mdx"

<IframeSwitcher
  id="backend-tools-example"
  exampleUrl="https://feature-viewer.copilotkit.ai/agno/feature/backend_tool_rendering?sidebar=false&chatDefaultOpen=false"
  codeUrl="https://feature-viewer.copilotkit.ai/agno/feature/backend_tool_rendering?view=code&sidebar=false&codeLayout=tabs"
  exampleLabel="Demo"
  codeLabel="Code"
  height="700px"
/>

<Callout>
  This example demonstrates the [implementation](#implementation) section applied in the <a href="https://feature-viewer.copilotkit.ai/langgraph/feature/agentic_chat" target="_blank">CopilotKit feature viewer</a>.
</Callout>

## What is this?

Tools are a way for the LLM to call predefined, typically, deterministic functions. CopilotKit allows you to render these tools in the UI
as a custom component, which we call **Generative UI**.

## When should I use this?

Rendering tools in the UI is useful when you want to provide the user with feedback about what your agent is doing, specifically
when your agent is calling tools. CopilotKit allows you to fully customize how these tools are rendered in the chat.

## Implementation

<Steps>
  <Step>
    ### Run and connect your agent
    <RunAndConnect components={props.components} />
  </Step>
<Step>
### Give your agent a tool to call

<Tabs groupId="language_agno_agent" items={['Python']} default="Python" persist>
    <Tab value="Python">
        ```python title="agent.py"
        from agno.agent import Agent
        from agno.models.openai import OpenAIChat
        from agno.tools import tool
        # ...

        # [!code highlight:6]
        @tool
        def get_weather(location: str):
            """
            Get the weather for a given location.
            """
            return f"The weather for {location} is 70 degrees."

        # ...

        agent = Agent(
            model=OpenAIChat(id="gpt-4o"),
            tools=[get_weather], # [!code highlight]
            description="A helpful assistant that can answer questions and provide information.",
            instructions="Be helpful and friendly. Format your responses using markdown where appropriate.",
        )
        ```
    </Tab>

</Tabs>
</Step>
<Step>
### Render the tool call in your frontend
At this point, your agent will be able to call the `get_weather` tool. Now
we just need to add a `useRenderToolCall` hook to render the tool call in
the UI.

<Callout type="info" title="Important">
  In order to render a tool call in the UI, the name of the action must match the name of the tool.
</Callout>

```tsx title="app/page.tsx"
import { useRenderToolCall } from "@copilotkit/react-core"; // [!code highlight]
// ...

const YourMainContent = () => {
  // ...
  {/* [!code highlight:12] */}
  useRenderToolCall({
    name: "get_weather",
    render: ({status, args}) => {
      return (
        <p className="text-gray-500 mt-2">
          {status !== "complete" && "Calling weather API..."}
          {status === "complete" && `Called the weather API for ${args.location}.`}
        </p>
      );
    },
  });
  // ...
}
```

</Step>
<Step>
### Give it a try!

Try asking the agent to get the weather for a location. You should see the custom UI component that we added
render the tool call and display the arguments that were passed to the tool.

</Step>
</Steps>

## Default Tool Rendering

<DefaultToolRendering components={props.components} />
